USABusiness Systems & Analytics Lead
1 нед. назад
163.8k–182k USD / yearUSALeadOnsite
analyticsdata integrationbusiness systems
Lead implementation of business systems and analytics architecture ensuring seamless data flow and trusted reporting across teams.
О компании
- Video is 90% of the world's data. Most of it is invisible to machines. TwelveLabs builds the intelligence layer to change that. Our multimodal AI models understand video the way humans do — across sight, sound, and motion — and power production-scale AI workloads across media, entertainment, sports, security, and government.
- We have raised more than $210 million from NEA, Radical Ventures, Amazon, NVIDIA, Snowflake, Databricks, Index Ventures, NAVER Ventures, Korea Investment Partners, Quadrille Capital, Red Bull Ventures, and AI pioneers including Fei-Fei Li, Silvio Savarese, and Alexandr Wang.
- We are a global company, headquartered in San Francisco with offices in Seoul, New York, and London, and employees around the world. We believe the differences in our cultural, educational, and life experiences make our products stronger. Building technology that understands the world in all its complexity requires people who see it from every angle. We are looking for individuals who are driven by hard problems and want their work to matter. Come build it with us!
Обязанности
- As our Lead, Business Systems & Analytics , you will be the first dedicated business systems hire at TwelveLabs. Your job will be to implement enduring systems & analytics architecture across TwelveLabs. Clear systems of record, data that flows between them without human intervention, and a reporting layer every team can trust.
- This is deliberately a hybrid role. Roughly half of your time will be around systems. This involves owning the stack, running implementations, building integrations, and setting master data standards across the business. The other half is analytics - turning that clean data into the dashboards and metric definitions that leadership and the board actually run the company on. We are hiring for someone who wants both halves, because the two reinforce each other: nobody builds good reporting on a stack they don't understand, and nobody designs a good stack without knowing what has to come out the other end.
- You will report to the Head of Finance and start as an individual contributor with company-wide scope. Finance and the core business systems are the first priority, but this role is horizontal by design. GTM, People, and Engineering are all customers, and we expect you to operate credibly with any of them. As the function grows, this seat is the foundation for a team.
- Own the business systems architecture end to end. Define the system of record for every critical data object (customer, vendor, employee, entity, department, contract) and enforce it, so that the same question asked in two systems returns the same answer.
- Build and maintain the integrations between our core platforms
- Own master data integrity across a multi-entity, global corporate structure including chart of accounts, department and cost center mapping.
- Build the company's reporting and analytics layer in Databricks. We are laying ground truth for the company across all business metrics (ARR, burn, runway, headcount, gross margin, unit economics). Model them in the warehouse, and surface them in dashboards teams can self-serve from
- Lead systems evaluation and implementation projects: build the requirements, run the vendor evaluation, negotiate alongside Finance, manage the implementation, and own the post-launch adoption
- Automate manual workflows relentlessly, including agentic and AI-assisted automation, and document everything so the automation survives you rather than depending on you
- Act as the translator between technical and business stakeholders: you should be able to sit with a data engineer in the morning and a department head in the afternoon and be useful in both conversations. Pipeline and CRM data hygiene with GTM, headcount and compensation reporting with People, cost attribution and infrastructure spend with Engineering
- Establish the standards, documentation, and runbooks that let this function scale into a team
Требования
- 8+ years in business systems, BizOps, RevOps, analytics engineering, or finance systems, ideally spending a large amount of that time at a growth stage startup.
- Hands-on involvement, if not ownership, of core systems of record including ERPs, CRMs and HRIS’.
- SQL fluency and genuine comfort working in a cloud data warehouse; dbt or an equivalent transformation framework is a strong plus
- A track record of building integrations between systems, whether through native connectors, an iPaaS, or direct API work in Python or similar
- Experience with multi-entity and multi-currency data structures, and an appreciation for why entity attribution matters
- Demonstrated ability to work across functions with no formal authority — influence, clear communication, and follow-through
- A documentation instinct: you build for handoff, not for job security
- Strong intellectual curiosity and a desire to dive deep into cutting-edge multimodal foundation models
- Ability to be on-site at our San Francisco (Jackson Square) office at least three days a week
Условия
- 🤝 An open and inclusive culture and work environment
- 🚀 Work closely with a collaborative, mission-driven team on cutting-edge AI technology
- 🏥 Full health, dental, and vision benefits
- 🌴 Extremely flexible PTO and parental leave policy. Office closed the week of Christmas and New Years
- 💪 Monthly wellness stipend
- 📚 Annual Learning & Development stipend to invest in your growth
- 💼 Global offices in San Francisco and Seoul, and coworking office memberships for remote team members
- 🛂 VISA support where applicable
- 🚆 Transportation stipend (SF onsite only)
- 🍲 Daily lunch & dinner provided (SF onsite only)
Другое
- ERP: Campfire
- Expenses: Ramp
- Banking: JP Morgan Access
- EPM: Pigment
- CRM: HubSpot
- Payment Processing & Usage Metering: Metronome, Stripe & AWS Marketplace
- Data Warehouse & BI: Databricks